Predictive and distributed routing balancing (PR-DRB): high speed interconnection networks

Current parallel applications running on clusters require the use of an interconnection network to perform communications among all computing nodes available. Imbalance of communications can produce network congestion, reducing throughput and increasing latency, degrading the overall system performance. On the other hand, parallel applications running on these networks posses representative stages which allow their characterization, as well as repetitive behavior that can be identified on the basis of this characterization. This work presents the Predictive and Distributed Routing Balancing (PR-DRB), a new method developed to gradually control network congestion, based on paths expansion, traffic distribution and effective traffic load, in order to maintain low latency values. PR-DRB monitors messages latencies on intermediate routers, makes decisions about alternative paths and record communication pattern information encountered during congestion situation. Based on the concept of applications repetitiveness, best solution recorded are reapplied when saved communication pattern re-appears. Traffic congestion experiments were conducted in order to evaluate the performance of the method, and improvements were observed.

Suivi de l'adhésion thérapeutique des patients hypertendus ou dyslipi- démiques par les cercles de qualité médecins-pharmaciens [Monitoring drug adherence for hypertensive and dyslipidemic patients in networks of community-based pharmacists and physicians].

Patient adherence is often poor for hypertension and dyslipidaemia. A monitoring of drug adherence might improve these risk factors control, but little is known in ambulatory care. We conducted a randomised controlled study in networks of community-based pharmacists and physicians in the canton of Fribourg to examine whether monitoring drug adherence with an electronic monitor (MEMS) would improve risk factor control among treated, but uncontrolled hypertensive and dyslipidemic patients. The results indicate that MEMS achieve a better blood pressure control and lipid profile, although its implementation requires considerable resources. The study also shows the value of collaboration between physicians and pharmacists in the field of patient adherence to improve ambulatory care of patients with cardiovascular risk factors.

Aplicación de soporte para personal docente en dispositivo móvil: iPhone

Actualment és difícil no veure a gent de totes les edats amb algun tipus de Gadget electrònic. En forma de telèfons mòvils, GPS, agendes electròniques, reproductors de música, tablets o qualsevol altre dispositiu, el món digital ens aborda, la informació i les dades es digitalitzen i arriben fins a les nostres butxaques per ser accessibles en qualsevol moment. Es fa indispensable familiaritzar-se amb aquestes eines i per això s’introdueixen en els centres educatius de tot el món. En aquest projecte es combinen tots aquests fets per desenvolupar un herbari digital sobre un dispositiu mòbil, amb finalitat educativa i ús privat.

La llengua de l'enemic com a llengua pròpia: cultures translatives del paisatge indígena nord-americà

This research paper seeks to bring into view the present-day situation of Native-American narrative in English. It is divided into four chapters. The first deals with the emergence of what we might call a Native-American narrative style and its evolution from 1900 up until its particularly forceful expression in 1968 with the appearance of N. Scott Momaday’s novel House Made of Dawn. To trace this evolution, we follow the chronology set forth by Paula Gunn Allen in her anthology Voice of the Turtle: American Indian Literature 1900-1970. In the second chapter we hear various voices from contemporary Native-American literary production as we follow Simon J. Ortiz’s anthology Speaking for the Generations: Native Writers on Writing. Noteworthy among these are Leslie Marmon Silko and Gloria Bird, alongside new voices such as those of Esther G. Belin and Daniel David Moses, and closing with Guatemalan-Mayan Victor D. Montejo, exiled in the United States. These writers’ contributions gravitate around two fundamental notions: the interdependence between human beings and the surrounding landscape, and the struggle for survival, which of necessity involves the deconstruction of the (post-)colonial subject. The third chapter deals with an anthology of short stories and poems by present-day Native-American women writers, edited by Joy Harjo and Gloria Bird and entitled Reinventing the Enemy’s Language: Contemporary Native Women’s Writings of North America. It too exemplifies personal and cultural reaffirmation on a landscape rich in ancestral elements, but also where one’s own voice takes shape in the language which, historically, is that of the enemy. In the final chapter we see how translation studies provide a critical perspective and fruitful reflection on the literary production of Native-American translative cultures, where a wide range of writers struggle to bring about the affirmative deconstruction of the colonialised subject. Thus there comes a turnaround in the function of the “enemy’s language,” giving rise also to the question of cultural incommensurability.

Unconditioned responses and functional fear networks in human classical conditioning.

Human imaging studies examining fear conditioning have mainly focused on the neural responses to conditioned cues. In contrast, the neural basis of the unconditioned response and the mechanisms by which fear modulates inter-regional functional coupling have received limited attention. We examined the neural responses to an unconditioned stimulus using a partial-reinforcement fear conditioning paradigm and functional MRI. The analysis focused on: (1) the effects of an unconditioned stimulus (an electric shock) that was either expected and actually delivered, or expected but not delivered, and (2) on how related brain activity changed across conditioning trials, and (3) how shock expectation influenced inter-regional coupling within the fear network. We found that: (1) the delivery of the shock engaged the red nucleus, amygdale, dorsal striatum, insula, somatosensory and cingulate cortices, (2) when the shock was expected but not delivered, only the red nucleus, the anterior insular and dorsal anterior cingulate cortices showed activity increases that were sustained across trials, and (3) psycho-physiological interaction analysis demonstrated that fear led to increased red nucleus coupling to insula but decreased hippocampus coupling to the red nucleus, thalamus and cerebellum. The hippocampus and the anterior insula may serve as hubs facilitating the switch between engagement of a defensive immediate fear network and a resting network.

Synchronous versus asynchronous modeling of gene regulatory networks.

MOTIVATION: In silico modeling of gene regulatory networks has gained some momentum recently due to increased interest in analyzing the dynamics of biological systems. This has been further facilitated by the increasing availability of experimental data on gene-gene, protein-protein and gene-protein interactions. The two dynamical properties that are often experimentally testable are perturbations and stable steady states. Although a lot of work has been done on the identification of steady states, not much work has been reported on in silico modeling of cellular differentiation processes. RESULTS: In this manuscript, we provide algorithms based on reduced ordered binary decision diagrams (ROBDDs) for Boolean modeling of gene regulatory networks. Algorithms for synchronous and asynchronous transition models have been proposed and their corresponding computational properties have been analyzed. These algorithms allow users to compute cyclic attractors of large networks that are currently not feasible using existing software. Hereby we provide a framework to analyze the effect of multiple gene perturbation protocols, and their effect on cell differentiation processes. These algorithms were validated on the T-helper model showing the correct steady state identification and Th1-Th2 cellular differentiation process. AVAILABILITY: The software binaries for Windows and Linux platforms can be downloaded from http://si2.epfl.ch/~garg/genysis.html.

Future trypanosomatid phylogenies: refined homologies, supertrees and networks

There has been good progress in inferring the evolutionary relationships within trypanosomes from DNA data as until relatively recently, many relationships have remained rather speculative. Ongoing molecular studies have provided data that have adequately shown Trypanosoma to be monophyletic and, rather surprisingly, that there are sharply contrasting levels of genetic variation within and between the major trypanosomatid groups. There are still, however, areas of research that could benefit from further development and resolution that broadly fall upon three questions. Are the current statements of evolutionary homology within ribosomal small sub-unit genes in need of refinement? Can the published phylograms be expanded upon to form `supertrees' depicting further relationships? Does a bifurcating tree structure impose an untenable dogma upon trypanosomatid phylogeny where hybridisation or reticulate evolutionary steps have played a part? This article briefly addresses these three questions and, in so doing, hopes to stimulate further interest in the molecular evolution of the group.

Structural Analysis of Networks

Network analysis naturally relies on graph theory and, more particularly, on the use of node and edge metrics to identify the salient properties in graphs. When building visual maps of networks, these metrics are turned into useful visual cues or are used interactively to filter out parts of a graph while querying it, for instance. Over the years, analysts from different application domains have designed metrics to serve specific needs. Network science is an inherently cross-disciplinary field, which leads to the publication of metrics with similar goals; different names and descriptions of their analytics often mask the similarity between two metrics that originated in different fields. Here, we study a set of graph metrics and compare their relative values and behaviors in an effort to survey their potential contributions to the spatial analysis of networks.

Dynamic simulation of regulatory networks using SQUAD.

BACKGROUND: The ambition of most molecular biologists is the understanding of the intricate network of molecular interactions that control biological systems. As scientists uncover the components and the connectivity of these networks, it becomes possible to study their dynamical behavior as a whole and discover what is the specific role of each of their components. Since the behavior of a network is by no means intuitive, it becomes necessary to use computational models to understand its behavior and to be able to make predictions about it. Unfortunately, most current computational models describe small networks due to the scarcity of kinetic data available. To overcome this problem, we previously published a methodology to convert a signaling network into a dynamical system, even in the total absence of kinetic information. In this paper we present a software implementation of such methodology. RESULTS: We developed SQUAD, a software for the dynamic simulation of signaling networks using the standardized qualitative dynamical systems approach. SQUAD converts the network into a discrete dynamical system, and it uses a binary decision diagram algorithm to identify all the steady states of the system. Then, the software creates a continuous dynamical system and localizes its steady states which are located near the steady states of the discrete system. The software permits to make simulations on the continuous system, allowing for the modification of several parameters. Importantly, SQUAD includes a framework for perturbing networks in a manner similar to what is performed in experimental laboratory protocols, for example by activating receptors or knocking out molecular components. Using this software we have been able to successfully reproduce the behavior of the regulatory network implicated in T-helper cell differentiation. CONCLUSION: The simulation of regulatory networks aims at predicting the behavior of a whole system when subject to stimuli, such as drugs, or determine the role of specific components within the network. The predictions can then be used to interpret and/or drive laboratory experiments. SQUAD provides a user-friendly graphical interface, accessible to both computational and experimental biologists for the fast qualitative simulation of large regulatory networks for which kinetic data is not necessarily available.